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EE 465Probability for Electrical and Computer Engineers

3 credits · Electrical Engineering · Penn State

This course covers basic concepts in probability, including random variables, conditioning, independence, laws of large numbers, and statistical confidence. While covering these basic probability concepts, illustrative examples drawn from Electrical and Computer Engineering topics such as communications, signal processing, networking, image processing, and control systems will be used to show engineering applications of the probability and statistical theory. The course concludes with a module on linear filtering of wide-sense stationary processes, including in the frequency domain via power spectral density. The course consists of lectures and recitations. Recitations reinforce concepts learned in lecture through problem solving. Recitations are also used to study applications such as information theory and signal detection using binary hypothesis testing. Laboratory exercises demonstrate the use of software packages for simulation and calculations.

Before you enroll

Prerequisites

You need:

Where it fits

Where it sits in degree plans

One of the options in (1)

  • Environmental Health and Safety, Minor
What it opens up

Courses that list EE 465 as a prerequisite (4)

  • A-I 305 Algorithmic Foundations for Artificial Intelligence
  • CMPSC 348 Data Science and Machine Learning for Computational Sciences
  • CMPSC 449 Foundations of Natural Language Processing
  • CMPSC 489 Deep Learning for Computer Vision